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<h1><a href="prediction_v1_2.html">Prediction API</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="prediction_v1_2.hostedmodels.html">hostedmodels()</a></code>
</p>
<p class="firstline">Returns the hostedmodels Resource.</p>
<p class="toc_element">
<code><a href="prediction_v1_2.training.html">training()</a></code>
</p>
<p class="firstline">Returns the training Resource.</p>
<p class="toc_element">
<code><a href="#new_batch_http_request">new_batch_http_request()</a></code></p>
<p class="firstline">Create a BatchHttpRequest object based on the discovery document.</p>
<p class="toc_element">
<code><a href="#predict">predict(data, body)</a></code></p>
<p class="firstline">Submit data and request a prediction</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="new_batch_http_request">new_batch_http_request()</code>
<pre>Create a BatchHttpRequest object based on the discovery document.
Args:
callback: callable, A callback to be called for each response, of the
form callback(id, response, exception). The first parameter is the
request id, and the second is the deserialized response object. The
third is an apiclient.errors.HttpError exception object if an HTTP
error occurred while processing the request, or None if no error
occurred.
Returns:
A BatchHttpRequest object based on the discovery document.
</pre>
</div>
<div class="method">
<code class="details" id="predict">predict(data, body)</code>
<pre>Submit data and request a prediction
Args:
data: string, mybucket%2Fmydata resource in Google Storage (required)
body: object, The request body. (required)
The object takes the form of:
{
"input": {
"csvInstance": [
"",
],
},
}
Returns:
An object of the form:
{
"kind": "prediction#output",
"outputLabel": "A String",
"id": "A String",
"outputMulti": [
{
"score": 3.14,
"label": "A String",
},
],
"outputValue": 3.14,
"selfLink": "A String",
}</pre>
</div>
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